Transthyretin cardiac amyloidosis (ATTR-CA) is an increasingly recognized disease that often results in heart failure and death. Traditionally, biological staging systems are used to stratify disease severity. Reduced aerobic capacity has recently been described as useful in identifying higher risk of cardiovascular events and death. Assessment of lung volume via simple spirometry might also hold prognostic relevance. We aimed to assess the combined prognostic value of spirometry, cardiopulmonary exercise testing (CPET) and biomarker staging in ATTR-CA patients in a multi-parametric approach. We retrospectively reviewed patient records with pulmonary function and CPET testing. Patients were followed until study endpoint (MACE: composite of heart-failure-related hospitalization and all-cause death) or censure (1 April 2022). In total, 82 patients were enrolled. Median follow-up was 9 months with 31 (38%) MACE. Impaired peak VO and forced vital capacity (FVC) were independent predictors of MACE-free survival, with peak VO < 50% and FVC < 70% defining the highest risk group (HR 26, 95% CI: 5-142, mean survival: 15 months) compared to patients with the lowest risk (peak VO ≥ 50% and FVC ≥ 70%). Combined peak VO, FVC and ATTR biomarker staging significantly improved MACE prediction by 35% compared to ATTR staging alone, with 67% patients reassigned a higher risk category ( < 0.01). In conclusion, combining functional and biological markers might synergistically improve risk stratification in ATTR-CA. Integrating simple, non-invasive and easily applicable CPET and spirometry in the routine management of ATTR-CA patients might prove useful for improved risk prediction, optimized monitoring and timely introduction of newer-generation therapies.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10254011PMC
http://dx.doi.org/10.3390/jcm12113684DOI Listing

Publication Analysis

Top Keywords

risk stratification
8
transthyretin cardiac
8
cardiac amyloidosis
8
higher risk
8
biomarker staging
8
attr-ca patients
8
50% fvc
8
risk
7
patients
6
stratification transthyretin
4

Similar Publications

While deemed potentially curative, surgical resection of hepatocellular carcinoma (HCC) is associated with >70% risk of post-operative relapse. Recurrence is uniquely multifactorial in HCC, potentially stemming from metachronous re-occurrence of the original tumor or de novo cancerization. Circulating tumor DNA may improve personalized risk stratification post-resection, a setting where adjuvant immunotherapy has failed to provide survival benefits.

View Article and Find Full Text PDF

Background: Right ventricular (RV) failure is a well-recognized pivotal prognostic factor of adverse outcomes in pulmonary artery hypertension (PAH), while RV dilation provides significant implications for adaptive or maladaptive changes. PAH is a predominant cause of mortality among patients with connective tissue disease (CTD). This study aims to elucidate the prognostic significance of RV morphology, as assessed by echocardiography (ECHO), in with CTD associated with PAH (CTD-PAH).

View Article and Find Full Text PDF

Cardiovascular disease remains a prominent cause of disability and premature death worldwide. Within this spectrum, carotid artery atherosclerosis is a complex and multifaceted condition, and a prominent precursor of acute ischaemic stroke and other cardiovascular events. The intricate interplay among inflammation, oxidative stress, endothelial dysfunction, lipid metabolism, and immune responses participates in the development of lesions, leading to luminal stenosis and potential plaque instability.

View Article and Find Full Text PDF

Early prediction and risk stratification of ovarian cancer based on clinical data using machine learning approaches.

J Gynecol Oncol

December 2024

Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric and Gynecologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.

Objective: Our study was aimed to construct a predictive model to advance ovarian cancer diagnosis by machine learning.

Methods: A retrospective analysis of patients with pelvic/adnexal/ovarian mass was performed. Potential features related to ovarian cancer were obtained as many as possible.

View Article and Find Full Text PDF

Background: Data on the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) for long-term outcomes are limited.

Methods And Results: A retrospective pooled analysis of individual patient data was performed. Deep-learning-based CT-FFR was calculated.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!